ABSTRACT: Mining in highly fractured ground at the Turquoise Ridge underground mine in Nevada presents challenges to maintaining long-term development and ore headings. The ground conditions at Turquoise Ridge require a variety of excavation techniques to successfully mine and maintain safe working conditions. Ground squeezing rates at Turquoise Ridge have been monitored with cross drift extensometers over the last 12 years and, more recently, with MPBXs and smart cables. Squeezing rates have ranged from 1 inch per year to over 1 inch per week, depending on ground conditions and mining history. Over time, squeezing ground causes damage to existing ground support, necessitating rehab for damaged areas. Areas of responsibility are assigned amongst our supervisors to help identify areas that need rehab, and this process allows us to effectively track rehab areas in the mine and schedule the rehab work. Geotech drilling and the RMR block model are effective tools used when designing drifts in the mine. Prediction of the rock strengths allows long-term drifts to be placed in harder rock with reduced rates of squeezing. In cases where mining through ground with a low rock mass rating is unavoidable, spiling and shotcrete arches are used to manage the increased squeezing rate. This paper reflects techniques that have been used to enhance safety in our travel ways by effectively monitoring and managing squeezing ground at Turquoise Ridge.

ABSTRACT: Vale Canada Limited has been operating underground mines in the Sudbury basin for over a century. The maturity of the operations is reflected in the amount of ore that has been mined and the number of associated sill pillars which have been formed in various orebodies at different mines. Sill pillars, or diminishing pillars, experience a significant increase in mining induced stress that has resulted in extensive seismicity, including some major seismic events. A large number of mitigation strategies, including both strategic and tactical control measures, have been developed at Vale's Ontario Operations to manage and control the risks associated with high stress conditions and seismicity in these pillars. This paper will focus on destress blasting, one of the tactical ground control measures, that used to reduce high stress concentrations in selective sill pillar geometries at two of Vale's mines. Four case studies, including three in the 100/900 orebodies at Copper Cliff Mine with the open stoping mining method, and one in the 153 orebody at Coleman Mine with both the overhand and underhand cut and fill mining method, are presented in this paper. These case studies demonstrate the de-stress blasting program that was executed in two different sill pillars to divert increased stress conditions away from active workings towards the abutments of the orebody. Specific topics, including de-stress blast design, an evaluation of blasting efficiency, de-stressing effectiveness, field monitoring results and lessons learned, are also discussed in this paper. Lessons learned from these case studies can be used for future de-stressing design in highly-stressed ground at deep mines.

ABSTRACT: The objective of this paper is to examine the applicability of the rockburst proneness criteria by using the numerical modeling tool. Many rockburst criteria are illustrated by the case of a deep coal mine in France, in which pillarburst (RC2) took place in 1993 in the shaft station, which is located at 1000 m from the earth's surface and it was excavated in 1984 by using the room-and-pillar mining method. The shaft station is surrounded by several longwall panels that were exploited between 1984 and 1994. To assess the stress redistribution and the stored strain energy concentration due to mining operations, a detailed large-scale finite difference numerical model of the mine has been constructed. The excavations in the numerical model are performed into two steps. Firstly, the shaft station galleries’ are excavated to determine their effect on the bursted pillar (RC2). Then, the longwall panels are excavated year by year to detect their effect on the shaft station pillars’. The numerical modeling results show that the vertical stress increased on the pillars due to the excavation of the longwall panels. To assess the pillarburst proneness in the shaft station area, the energy-based rockburst criteria (i.e., Loading System Stiffness (S)) are found to be more efficient than the stress-based rockburst criteria (i.e., Brittleness coefficient (B)).

ABSTRACT: The essential task for management of rock related risks in mines is to continuously confirm that the mine is safe. For small scale, day to day hazards observational methods comprising planned triggers, responses and reviews is formalized and well-practiced but for large scale mine scale instability, large seismic events or inrushes the analysis and decision-making process during design and operations is harder to prescribe. Often, only the measurement and observation tasks at a mine are properly documented, and the ensuing analysis and critical remedial actions are not prescribed. In some mines it is unclear who is responsible for maintaining the ‘mine stability safety case’ and team members simply assume that the work to confirm the mine is safely stable is being undertaken by others. Too often, comprehensive databases of real time measurements are ignored by engineers until after a serious event.

ABSTRACT: This paper demonstrates two modifications to Heuer's (1995 and 2005) tunnel inflow calculation method that are intended to improve the accuracy of inflow estimates. The first improvement is concerned with updating the method of characterizing hydraulic conductivity. Rather than using an empirical histogram of packer test data results, multiple probability distributions are considered, and their fit evaluated using the method of L-moments. In addition, upper bounds are imposed on selected probability distributions to prohibit estimating unreasonable inflow rates. The second improvement highlights the importance of tunnel segment length for which each hydraulic conductivity estimate is applicable on bounding values of tunnel inflow within a stochastic framework. The magnitude of the tunnel segment length for this study is selected as the radius of rock mass affected by a packer test. When the tunnel segment length is increased above this value, the range of uncertainty in the total tunnel inflows increases. These two modifications are applied to a case study in the United Kingdom for two planned water conveyance tunnels being designed to convey cooling water from two planned new nuclear reactor units.

ABSTRACT: It is commonly assumed that the dimensions of an induced microseismic cloud around an Enhanced Geothermal System (EGS) well delineate the “stimulated volume” in which permeability has been increased. This interpretation derives from a self-propping fracture model, wherein shear slip results in some permanent increase of hydraulic aperture. Or, more simply, earthquakes equal permeability. In contrast, here, we interpret microearthquakes (MEQs) directly in terms of the stress and pressure conditions that control earthquake triggering. In many cases, triggering is dominated by fluid pressure changes within a fracture, although increasingly poroelastic and earthquake interaction effects are seen as important.

ABSTRACT: Characterization of unstable rock slopes can pose a high level of risk toward the engineer/geoscientist in the field due to inaccessibility and safety issues. During recent decades, rapidly developing remote sensing (RS) techniques, including Terrestrial Laser Scanning (TLS), Terrestrial Digital Photogrammetry (TDP), and Unmanned Aerial Vehicle Structure-from-Motion (UAV-SfM) are being progressively employed for landslide investigation and risk assessment. These methods allow acquisition of three-dimensional (3D) data sets from previously inaccessible terrain with sub-centimeter accuracy. We present an innovative approach to investigate the preliminary engineering geological characterization of a large (~5.5 Mm 3 ), destructive landslide that occurred on August 2 nd , 2014 near Jure village, ~70 km northeast of Kathmandu, Nepal. We conducted traditional field surveys (Geological Strength Index, scanline, etc.), RS techniques and preliminary 2D/3D numerical modelling with the objective of understanding conditioning factors, slope failure mechanisms, and future hazards. With four years of RS data, analysis of strength degradation and progressive weakening of the rock mass has been analyzed by linking erosional and depositional processes using 3D change detection algorithms. Results of 2D/3D rock engineering mapping and modelling have been integrated within an interactive 3D virtual/mixed reality (VR/MR) geodatabase model of the Jure field site, enabling an immersive and enhanced engineering 3D geovisualization experience. We demonstrate how VR/MR techniques can be employed to conduct/compare discontinuity mapping on virtual outcrops and advance the understanding/communication of landslide investigation and hazard/risk assessment.

ABSTRACT: Excavation in the complex geological structure often accompanies with water-inrush accidents, which is considered to be resulted from mass migration and loss in fractured rock in the seepage process. When granular matters migrate and lose, the grain size distribution (GSD) changes over time, it will in turn affect the migration and loss of fine matters. In this paper, the authors carried out seepage tests for rock granular matters considering mass migration and loss, discussed the GSD variation and derived a new GSD expression. The results indicate that (1) all the rock matters with different sizes change in the seepage process, no matter what the samples’ Talbot power exponent (TPE) is and what the compression condition is; (2) the residual mass ratios of samples without initial compression and the ones with initial compression of 10mm have the same variation tendency for rock matters with sizes of 0~10mm and 15~25mm, while they have the different variation tendencies for samples of 10~15mm; (3) the GSD varies from mass migration and loss in the seepage process; (4) the varied GSD obeys the like-Talbot continuous grading expression. The work can be applied as a technical reference for a potential seepage instability or water inrush disaster.

ABSTRACT: The accurate prediction of cement failure is significant to maintain wellbore integrity. In the downhole situations, the failure criteria widely used for rock are not guaranteed to be suitable for cement. Till now, seldom researchers have paid attention to the right choice of failure criterion for cement and most of them simply used the Mohr-Coulomb criterion. In this work, comprehensive research is performed to collect published conventional and true triaxial compression strength data of cement. All the accessible data are used to evaluate the accuracy of six different failure criteria. A machine learning algorithm is developed to generate cement parameters, such as cohesion and friction angle. The statistic value, Misfits, is used for the quantitative comparison of the accuracy of different failure criteria. Results show that using only the conventional triaxial strength data, the influence of intermediate stress cannot be reflected and Mohr-Coulomb could provide similar accuracy compared to the three stress dependent criteria. However, when the true triaxial compression strength data is applied, the Mohr-Coulomb could generate significant errors. Three stress dependent criteria should be used for predicting cement failure. This study fills the gap of finding the right failure criterion for cement and provides guidance for wellbore integrity.

ABSTRACT: Elastic properties of rocks including Young's modulus and Poisson's ratio, in specific, are the main parameters, which are needed for design of hydraulic fracturing geometry, estimation of stimulated hydraulic fracture volume, sanding prediction and design of gravel pack and many other applications. Conventionally, the elastic properties are estimated from the compression and shear sonic and density logs, due to the intrinsic relationship of the sonic velocity and density with rock stiffness, then, calibrated against the core data taken at some depths. However, the use of any correlation is subjected to several shortcomings, including the fact that they cannot be generalized and in many cases quality cores are not available to conduct the calibration. In this study, we used the Artificial neural network (ANN) to estimate the elastic properties of the Bakken Formation. A total of 240 core samples from eight wells drilled into Upper, Middle and Lower Bakken were used. Bulk density, compressional and shear velocities, and porosity were the main parameters used for training purposes. The results indicated that an optimized ANN model is capable of predicting the elastic properties better than existing correlations using different technics in optimization and agreement study.

ABSTRACT: The National Institute for Occupational Safety and Health (NIOSH) first developed the Analysis of Retreat Mining Pillar Stability (ARMPS) program to help the U.S. coal mining industry to design retreat room and pillar panels. Similar to other pillar design methodologies, ARMPS determines the adequacy of the design by comparing the estimated in situ and mining induced loads to the load bearing capacity of the pillars. ARMPS calculates magnitude of the in situ and mining induced loads by using geometrical computations and empirical rules. The program uses the “abutment angle” concept in calculating the magnitude of the mining induced loads on pillars adjacent to a gob. The value of the abutment angle for coal mines in the United States was derived by back analysis of field measurements, and ARMPS2010 engineering design criterion was derived from the statistical analysis of the databases of more than 640 retreat mining case histories from various U.S. coal mines. In this study, stress measurements from U.S. and Australian coal mines were back analyzed using the square decay stress distribution method, and the abutment angles are investigated. The results of the analyses indicated that for shallow mines with overburden depths of less than 200 m, empirical derivation of 21° abutment angle used in ARMPS2010 was supported by the case histories. However, at depths greater than 200 m, the abutment angle was found to be significantly less than 21°. A new equation employing the overburden depth to panel width ratio was constructed for the calculation of abutment angle for deep cover cases. Finally, the new abutment angle equation was tested using 336 deep cover cases from the ARMPS2010 database. The new abutment angle equation was found to perform a good classification compared to using 21°. It was also apparent that, for deep cover cases (deeper than 200 m), the barrier pillar stability factors were the governing parameters in classification of failed cases and the results can be considered an indicator for the importance of barrier pillars in deep cover retreat mines.

ABSTRACT: In order to generate a full-scale, real world data set for calibration purposes for the rockfall simulation program RAMMS::ROCKFALL, we conducted extensive single block induced rockfall experiments with blocks of 200/800/2670 kg (~440/1760/5890 lb). With a fully four-dimensional trajectory reconstruction, we are able to retrieve the full set of parameters of interest on the single block rockfall trajectories such as translational velocity vectors, angular velocities, impact duration and forces, ballistic jump heights and lengths. This invaluable information can now be used for calibration purposes of the rockfall simulation code kernel, matching simulation performance to experimental results. Here, we present experimental data of the wheel shaped norm test rock EOTA 221/780kg , its reconstruction methodologies and subsequent calibration routines, with the aim to reduce the risks of inaccurate modelling caused by insufficiently calibrated models.RAMMS::ROCKFALL is the rockfall module in the RAMMS-Software suite ( RA pid M ass M ovement S imulation). It applies a novel contact-algorithm to model rockfalls, as opposed to most other rockfall simulation programs relying solely on restitution coefficients. The model accounts for real rock shapes, computing their runout trajectory over 3D terrain, including their jump heights, velocity, rotational velocity, rotational and total kinetic energy. All possible modes of rockfall motion (jumping, rolling and sliding) are deterministically simulated. Dynamics of single trajectories can be individually inspected or sets of multiple trajectories can be statistically analyzed.

ABSTRACT: Rockfalls present a major safety threat in open-pit mining operations and transportation corridors. The sudden onset of rockfall events makes it difficult, if not almost impossible, for conventional monitoring methods to provide adequate pre-warning, resulting in a challenge for mine operators and planners. One of the major challenges for geotechnical engineers is the ability to model the trajectory and run out distances or rock blocks in order to properly map the risks associated to the occurrence of such events and to properly design catch benches and exclusion zones. Several modeling tools are available today for this purpose, but they are often poorly supported and calibrated with instrumental data. One of the most common methods currently used consists in localizing the detachment and accumulating areas by comparing 3D models generated by LiDAR scans. The major drawback of this method is that the information that is collected is post-event and cannot provide data about the dynamics of the rockfall events. IDS GeoRadar has recently developed an innovative radar system able to locate and track rockfalls in real-time, from a distance up to 2000 m from the slope by simultaneous coverage of a wide portion of the highwall. The new radar system is able to generate quick alerts immediately after the detachment of the initial rock blocks and will provide beneficial information with regards to statistical data on the occurrence in space and time, travel path, velocity, run out distance, and size of blocks. This paper describes the new technology, initial results from field tests conducted on a natural slope near Tschamut, Switzerland, and recommendations for future work.

ABSTRACT: The Valley of the Kings (also known as King's Valley, KV) in Egypt is recognized as one of the richest archeological world heritage sites. Thousands of tourists visit the valley each day and its rock-cut tombs, of which many were excavated close to or into the steep cliffs of the valley. The rock mass properties and environmental conditions of the area were gathered from literature to conduct a preliminary stability assessment of the fractured cliff above the 18 th Dynasty tomb KV42 constructed for Hatshepsut-Meryet-Ra, the wife of Thutmose III, reused by a mayor of Thebes, Sennefer, and his family members. A 2D numerical model was developed in RS2® using the Shear Strength Reduction (SSR) modelling method, which indicates the importance of vertical fractures on the cliff stability. Preliminary results suggest that failure could be more influenced by the orientation of vertical joint sets rather than bedding planes. We installed a monitoring station to record the local environmental parameters such as temperature and relative humidity along with crack meter readings and discuss the impact of daily and seasonal climatic variations on vertical discontinuity opening and closing cycles. A coupled thermal and geomechanical model is recommended to be developed in further stages of this research to validate the effects of climatic variables on the extension of fractures and cliff stability at KV42.

ABSTRACT: The ability to monitor mining-induced ground deformation is an integral part of a Ground Control Management Plan (GCMP) in any underground mine. The integration of such monitoring into an early warning program, coupled with an instantaneous response plan for potentially hazardous conditions, contributes to a safer working environment. There is now a user-friendly monitoring device which allows any worker in the area of a ground movement hazard to be immediately alerted by color changing LED lights. Using this system, no special engineering skills or knowledge are required to recognize the indication of a potential hazard. The system is tamper proof and can only be replaced once the area is declared safe by a competent professional. The movement of the rock mass exceeding a pre-determined limit is accurately quantified by these devices. Therefore, the in situ ground movement monitoring can be used to calibrate numerical modeling and to evaluate designed support efficiency. This better understanding will enable operations to make informed decisions regarding the selection of support systems and the effect of mining rate and excavation proximities

ABSTRACT: The geometry of hydraulic fractures is a major concern, especially in highly fractured reservoirs, once it can severely affect oil productivity. Furthermore, interaction of hydraulic fractures with natural fractures can affect locally the in-situ stress state that may cause slippage of the natural fracture. In some cases, stress shadowing effects can even close the hydraulic fracture. Stress rotation around the natural fracture can make hydraulic fracture geometry complex, demanding more computational capacity and time to run numerical simulations. The neural network is a tool that can help real time daily operations when a quick decision is necessary and there is no time to run numerous simulations. This paper focuses on the development of an artificial neural network to predict the interaction between natural and hydraulic fractures. The artificial neural network predicts if hydraulic fractures cross or open natural fractures. In-situ stresses, fracture energy, friction angle of the natural fracture, and angle of approach between fractures are the required input for the artificial neural network, while mode of interaction such as opening, or crossing is the output. The database to train the neural network includes experimental data available in literature and results from numerical simulations. A considerable number of numerical simulations using interface elements to represent fractures provide a suitable database to build an accurate neural network. The neural network was trained for predicting fracture interaction with more than 90% accuracy for opening or crossing behavior. Results were compared with experimental data available in literature and numerical simulations. The results show that for higher angles of approach and higher stress differential, there is a strong tendency to fracture crossing. This is in agreement with the experimental conclusions presented by previous publications in the literature. Additionally, intermediary stress differentials, low values of cohesion and friction angle, and approach angle below 60° define conditions with a strong tendency to open the natural fracture. The scenarios predicted by the neural networks is in agreement with the rock mechanics concepts and with the expected tendencies, which gives more reliability to the neural network.

ABSTRACT: Rock bolt is one of the major support systems of tunnel engineering. It is used to stabilize suspended rock blocks around an excavation section, reinforce rock mass, and reduce displacement along rock joints. This study proposed a rock bolt model, which includes two parts: a bolt body and interface. The bolt body is made of raw bonded ball elements, and interfaces between the rock bolt and surrounding rock mass are simulated using a smooth-joint model The proposed model was first verified using laboratory pull-out and shear tests. Simulation results were consistent with experimental results in terms of a force–displacement curve and failure morphology. A series of tunnel cases were further simulated. The results showed that the proposed model can simulate rock bolt functions on tunnel excavation. Furthermore, the results showed that increasing the length and number of rock bolts increases the reinforced effect; however, as the length and number of rock bolts increased to an upper bound value, a limited increment was observed in the reinforced effect. The proposed model provides a useful tool to simulate the rock bolt system for tunnel engineering.

ABSTRACT: This study has analyzed 3D stress and displacement distributions around a retreating longwall face intercepted by a geological fault. Analyses considered longwall set-up and development entries, and the longwall face. Linear elastic rock mass behavior was used for analysis except in areas adjacent to the fault where non-linear Hoek-Brown failure criterion was used. Data analyses along several lines in the roof and floor included roof-to-floor displacements and stress concentration factors. The displacements across the face in set-up entries were 35% larger with the fault present. Similar data parallel to the face advance varied with the face location. Vertical displacements were similar for this specific fault orientation. Similar analyses are also included for development entries and T-junctions. These data were compared with field measurements in longwall set-up and development entries.

ABSTRACT: Parameter calibration is an indirect problem in which responses of a system are known, but the properties of the said system are not. Often, trial and error strategies are used for parameter calibration. However, they can be labor intensive and time consuming. Machine learning methods have been employed to automatize the process. The present work proposes a combination of Genetic Programming (GP) with an optimization method to estimate the elastic parameters of a finite element model of an oil and gas field. The estimated parameters were the Young's modulus and the Poisson's ratio of each rock layer and the target responses were the field measurements of horizontal and vertical total stress profiles and the maximum surface subsidence. GP provided functions relating each response to the elastic properties. An optimization procedure using the interior-point algorithm was applied in order to estimate the values for the properties that would lead to the target outputs. Results show that the calibration procedure provided properties that, in most cases, differed in less than 10% from the expected values. Thus, the proposed method has potential to be a relatively straightforward method to estimate parameters of a geomechanical model.

ABSTRACT: Fiber optic based distributed acoustic sensors (DAS) provide a new approach for monitoring signals of interest in the subsurface with unprecedented spatiotemporal resolution. These sensors produce measurements that are fundamentally different from their traditional counterparts, such as geophones, and produce significantly larger volumes of data. To interpret these data, we begin by using the physics-based thermal-hydraulic-mechanical (THM) model in the GEOS code to simulate synthetic DAS measurements for a range of subsurface conditions (fracture propagation, fault slip, etc.) and sensor configurations (e.g.: horizontal or vertical well deployments). These synthetic DAS measurements are then algorithmically labeled based upon features of interest within their parent models, such as the extent of any generated hydraulic fractures or the distribution of proppant particles, and are compiled into a database. The synthetic database can be used to train and test an initial deep neural network (DNN) representation of the subsurface, which can then be optimized by incorporating any available field measurements through transfer learning. This hybrid, physics informed DNN model is capable of interpreting DAS measurements in near-real time, making it a useful tool for decision making by field engineers, and works under both data-rich and data-poor conditions. To demonstrate this approach, we consider the problem of imaging hydraulic fracture propagation in an unconventional oil and gas reservoir. Our results indicate that we are can use a trained DNN model to accurately estimate the extents of a hydraulic fracture using the location information and DAS measurements for a single fiber-optic sensor as inputs.